As microelectronic device feature sizes continue to shrink, it is necessary to have tighter controls to maintain high yields. Such tighter controls begin at a tool level. A conventional tool 100 is schematically shown in FIG. 1. The tool 100 can include an etcher, depositor, polisher or the like. Any combination of these can also be included in the tool. A typical tool is controlled by a tool controller 103 which communicates with a factory controller via a communication port 105. In particular, the tool controller 103 may receive process recipes from the factory controller via the communication port 105 and process wafers in accordance with the received recipes.
The tool 100 can be controlled on a run-to-run control basis for various semiconductor manufacturing processes. The run-to-run control reduces unacceptable variations of outputs (i.e., wafers processed by the tool) from targets. In the run-to-run control of such a tool, the process recipe is modified between process runs so as to minimize process drift, shift, and variability.
Creating accurate and precise run-to-run control starts from designing and running experiments on the tool for an eventual modeling of the tool. Designing a set of experiments is called DOE (Design of Experiments). A good DOE establishes the relationship between variables that may have a predictable impact on the processing output a user wishes to control, e.g., one or more film properties such as film thickness, while keeping the required number of experiments low.
Conventionally, a DOE system 107 configured to generate a DOE plan that includes a set of experiments is typically not integrated with the tool 100. Hence, the experiments of the DOE plan are run on the tool 100 by a user manually setting up the tool 100. When the experiments of the DOE plan are run, data relating to process recipe parameters and process outcome are collected. The collected data are then used in creating one or more models in a modeling environment 109.
Conventionally, the modeling environment 109 is also not integrated with the tool 100. In the modeling environment 109, the models are created, and the models can be represented as raw data that reflects the tool, or it can be represented by equations, for example, multiple input-multiple output linear, quadratic and general non-linear equations, which describe the relationship among the variables of the tool 100.
The DOEs, models and eventual run-to-run control of tools are, conventionally, performed on a lot-to-lot basis. This is because it is difficult to collect the data from different tools, put them together and control experiments at a wafer-to-wafer level. As noted above, the tool 100, DOE system 107, and modeling environment 109 are not integrated together. Therefore, once a DOE plan is created, its experiments are run manually on the tool 101 and the resulting data are collected manually. Even if the DOE data are collected electronically, it needs to be reformatted to be used in the modeling environment 109. This also means that there cannot be any automated coordination between the DOE systems 107 and modeling environment 109. These shortcomings made the use of the DOEs a difficult process for a user of the tool 100.